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Mining Association Rules from XML Data
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Author(s):
Qin Ding (East Carolina University, USA)and Gnanasekaran Sundarraj (The Pennsylvania State University at Harrisburg, USA)
Copyright:
2008
Pages:
13
Source title:
Data Mining and Knowledge Discovery Technologies
Source Author(s)/Editor(s):
David Taniar
(Monash University, Australia)
DOI:
10.4018/978-1-59904-960-1.ch003
Keywords:
Data Mining
/
Data Mining and Databases
/
Information Science Reference
/
Library & Information Science
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Mining Association Rules from XML Data
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Abstract
With the growing usage of XML in the World Wide Web and elsewhere as a standard for the exchange of data and to represent semi-structured data, there is an imminent need for tools and techniques to perform data mining on XML documents and XML repositories. In this chapter, we propose a framework for association rule mining on XML data. We present a Java-based implementation of the Apriori and the FP-Growth algorithms for this task and compare their performances. We also compare the performance of our implementation with an XQuery-based implementation.
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